Metabolic regulation is essential for homeostasis and for resilience in the face of external threats. Hormones play key roles in metabolic regulation, and, therefore, in maintaining homeostatic resilience. Although it is clear that many hormones decline with increasing age at the population level, analysis of individual trajectories involving multiple timepoints has never been performed. Therefore, the question of the predictive value of individual trajectories remains unanswered. IGF-1 and DHEAS represent excellent candidates for trajectory analysis: each corresponds to a distinct hormonal pathway; both have diverse effects on physiologic systems critical for functional aging (e.g., cardiovascular, musculoskeletal, and neurologic); and both, at the population level, decrease with age. Our central hypothesis is that trajectories of change inIGF-1 and DHEAS individually and jointly predict health, function, and survival in old age. We propose to evaluate this hypothesis using data from the Cardiovascular Health Study (CHS), an established, well-characterized, prospective, NIH-sponsored longitudinal study of community-dwelling men and women over the age of 65. Existing data collected over a 16-year follow-up period, with banked blood specimens at eight timepoints over this time span, are available for the proposed analyses.We hypothesize that those who have no decline in their hormonal levels over time will have greater survival and retain higher levels of function with aging than those whose trajectory demonstrates an overall decline and those who have extreme variability in hormonal levels overtime. This study proposes the following research aims: 1) to define the prevalence of the predominant patterns of trajectories of IGF-1 and DHEAS and to determine the association of each trajectory pattern with health and survival, 2) to determine differences between men and women in their trajectory patterns, 3) to establish whether the baseline values alone, the independent trajectories alone, or the independent trajectories plus the baseline values are the best predictors of health and survival, 4) to define the impact of adverse events and exercise on the trajectory, and 5) to determine the impact of joint abnormalities in trajectory patterns of IGF-1and DHEAS. This research is a novel application of endocrine models of homeostasis and trajectory analysis to studying the biology of aging at the population level. Our work will directly guide the selection of the appropriate population for growth hormone analogues and DHEA.